                                                                               CGD NOTE 385 | DECEMBER 2025

GEMs and the 600800 Billion Dollar
Data Dividend

     Karen Mathiasen and Nico Martinez

For years now, stakeholders from the private, public, and official sectors have campaigned for the
release of data from the Global Emerging Markets Database (GEMs) consortium, which tracks the
default and recovery rates of borrowers from 29 development finance institutions (DFIs) including
the major multilateral development banks (MDBs). This persistence paid off: the GEMs consortium
just released its most comprehensive dataset, disclosing 40 years of data for lending to governments
and 30 years of data for lending to state-owned enterprises and the private sector.

One motivation behind the public data push was so other stakeholders, including investors and
credit rating agencies (CRAs), could see that lending to emerging markets and developing economies
(EMDEs) is less risky than often perceived for transactions involving MDBs and DFIs. Indeed, based on
the latest data set, a key observation of the GEMs consortium is that EMDEs' sovereign credit ratings
significantly overstate the default risk of private projects structured by MDBs and DFIs. The average
default rate of sovereigns over four decades was only 0.77 percent, with recovery rates of 95 percent.
Data on state-owned enterprises show more volatility but are still low, with average default and
recovery rates of 2.6 percent and 88 percent respectively between 1994 and 2024. For the private
sector, default rates averaged 3.5 percent and recovery rates averaged 73 percent, although median
recovery rates were above 90 percent.

There is some correlation between income levels and default rates, with Europe and Central Asia
usually on the low end, and higher rates prevailing in sub-Saharan Africa (SSA): as an example,
average defaults for lending to the private sector in Europe and Central Asia were 2.7 percent
compared to 6 percent for SSA. But recovery rates do not appear associated with country income
levels: median recovery rates for SSA are 97.8 percent and 86.5 percent for Europe and Central Asia.

This data disclosure has already proven hugely consequential because Standard & Poor's has
announced that factoring newly available GEMs data into their assessments of MDB portfolio risk
had a big impact on MDB capital requirements under their methodology: they now estimate that the
major MDBs are sitting on an extra $600$800 billion in lending capacity that could be deployed over
the next ten years without putting their ratings at risk. This extraordinary result underscores why
data transparency is so important. Just by providing more information about their own credit track
records, MDBs can drive much more accurate assessments of risk--to their benefit and to the benefit
of private investors.

The campaign for GEMs

The first major public push for GEMs data came in the 2022 report, "Boosting MDBs' Investing
Capacity," (also known as the Capital Adequacy Report, or CAF). The report was prepared by an
independent experts' group commissioned by the G20 to identify ways to use MDB capital more
efficiently while maintaining high institutional ratings. Included among its recommendations was
a call to provide public access to GEMs data, with the authors arguing that: "Wider access to GEMs
would build investor understanding and strengthen risk assessment, expanding investor interest
and better risk transfer opportunities for MDB assets, improving capital efficiency and scaling
capacity for MDBs" (italics ours).

GEMs data are privileged: only the member DFIs have access. Stakeholders argued that because the
data are collected by donor-funded institutions, they should be in the public domain. This proved
easier said than done. Securing access to GEMs data at a level granular enough to be of value to CRAs
and investors requires a highly disaggregated and fully scrubbed database, harmonized across
institutions, while still maintaining business confidentiality for individual projects.

Initial data disclosures were too aggregated to be of much use. But after considerable internal
deliberations and external urging, the GEMs consortium released data by region, sector and year for
sovereign and sovereign-guaranteed loans and state-owned enterprises (i.e., companies with at least
50 percent public ownership) and by country for private lending. To preserve anonymity in line with
non-disclosure agreements required by underlying contracts, there are some gaps--especially at the
sector level--but overall, these data offer considerable insights into the risk profiles of MDB and DFI
borrowers. To enable even more fulsome datasets going forward, we believe these contracts should
explicitly allow for more data disclosure.

Key findings--sovereign and sovereign guaranteed
lending

What GEMs data show across the board is that MDB lending risks are relatively low, including in
most low and lower-middle-income countries (LICs and LMICs), for all categories (sovereign, SOE,
and private). Starting with sovereign lending, data over four decades show that loan repayments
have been consistently near or at 100 percent, with average default rates of only 0.77 percent. High
repayment rates are to be expected--the MDBs benefit from preferred creditor status and once a
country defaults to an MDB, access to capital markets is usually cut off. Restoring credibility as a
borrower requires making good on these payments, which is why recovery rates are also very high, at
95 percent on average, regardless of region or lending volumes. (See Figures 1 and 2.)

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND  2
Figure 1: The average sovereign and sovereign guaranteed debt default rate was
~0.8 percent, with an average 95 percent recovery rate
Average sovereign debt default and recovery rates across World Bank regions,
1984-2024

Source: Global Emerging Markets Risk Database  *The sample size of South Asian defaults is too small to produce a meaningful
recovery rate statistic.

Figure 2: Which countries have the highest volume of sovereign debt?
Signed sovereign debt by country, 19842024

Source: Global Emerging Markets Risk Database.

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND  3
Key findings--lending to state-owned enterprises

For state-owned enterprises (i.e., municipalities and companies that are at least 50 percent state-
owned), GEMs reported an overall default rate of 2.6 percent between 1994 and 2024. No defaults
were recorded for South Asia, but the number and volume of contracts is low relative to other regions:
221 deals worth 2.9 billion euro. Default rates were highest in sub-Saharan Africa, at 5.2 percent, but
this is for 3,265 contracts valued at nearly 86 billion euro. (See Figures 3 and 4.)

The large number of contracts in sub-Saharan Africa enabled GEMs to provide a sectoral breakdown
for SOE default rates. The sectors are too broadly defined to offer major insights but the data we have
indicate that default risks are not highly variable: financial institutions (5.2 percent), non-financial
institutions (5.2 percent), banking (6.4 percent), non-bank financials (3.5 percent), infrastructure
(5 percent) and services (6.1 percent).

Average SOE loan recovery rates between 19942022 were 86 percent, exceeding 80 percent in
four of the five regions of operation. (Recovery rates for 2023 and 2024 are not disclosed, as defaults
during this time remain unresolved.) Sub-Saharan Africa accounts for nearly 58 percent of the
recoveries, with an overall average rate of 87 percent. Interestingly, the lowest average rate of
recovery was in East Asia and the Pacific, at 73.5 percent. (See Figure 3.)

Figure 3: The average SOE borrowing default rate was ~2.6 percent, with an
average recovery rate of ~86 percent
Average default and recovery rates for SOE borrowing across World Bank regions,
1994-2024*

Source: Global Emerging Markets Risk Database *Recovery rate statistics are up to 2022, as 2023 and 2024 defaults from those
years are still being resolved. **MENA region SOE borrowing default rates are not available in the GEMs data. ***South Asia
recorded zero defaults in this category during the study period, so there is no recovery rate for the region.

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND                                                                            4
Figure 4: Sub-Saharan Africa had the highest volume of SOE borrowing, with
surprisingly low volumes reported for South and East Asia

Signed amount of SOE borrowing by World Bank region, in EUR millions (1994-2024)

Source: Global Emerging Markets Risk Database.

Key findings--lending to the private sector

For the private sector, we have data by region and country--a first. GEMs looked at 15,500 contracts
between 19942024 from 169 countries and found that the average default rate was 3.5 percent,
which GEMs reports is on par with B-rated companies from S&P and B3 rated companies from
Moody's, where default rates are 3.3 and 4 percent respectively. These are similar to many corporate
borrowers from advanced economies.

As one might expect, default rates on MDB credits to private companies are negatively correlated
with country income levels: the average default rate in UMICs was 2.7 percent, compared to
3.8 percent in LMICs, and 7.1 percent in LICs. Europe and Central Asia had the lowest default rates
(2.7 percent) and sub-Saharan Africa the highest (at 6 percent). The average SSA default rate is
comparable to that of S&P B to B- rated companies in advanced countries. Corporate borrowing rates
for such companies have averaged between 6.5 and 8 percent since the start of 2024, as compared to
SSA borrowing rates of ~8 to 8.5 percent over the same period.

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND                                5
Figure 5: The average private loan default rate across countries was ~3.5 percent,
with an average recovery rate of ~73 percent

Average private loan default and recovery rates across World Bank regions,
1994-2024

Source: Global Emerging Markets Risk Database.

Recovery rates averaged 73 percent, although median recovery rates were above 90 percent,
suggesting that a few large transactions may have dominated. Interestingly, and in contrast to
default rates, recovery rates do not necessarily rise with country income levels: the lowest level--
68 percent--was observed in Latin America and the Caribbean, while the highest average rate of
recovery was in sub-Saharan Africa, at 78 percent.

There are some data by sector and region for credits to the private sector, although significant
gaps make cross-regional comparisons challenging. Average default and recovery rates and
median recovery rates for all regions are provided for three sectors from 19942024: (1) consumer
discretionary (e.g., autos, apparel, home furnishings, electronics and leisure); (2) financials
(e.g., capital markets, real estate, insurance); and (3) materials (e.g., construction, chemicals, metals,
mining). Financials accounted for 36 percent of the overall loan portfolio and had the lowest default
rate at 2.3 percent. (See Tables 1 and 2.)

Default rates were lowest in Latin America and the Caribbean (LAC) for consumer discretionary
and materials (3.3 and 3.6 percent respectively), and in Europe and Central Asia for financials
(1.1 percent).

Average default rates were highest in sub-Saharan Africa for all three sectors: consumer goods,
11 percent, financials, 4 percent and materials, 6.8 percent. Notably, sub-Saharan Africa was the
only region where average default rates exceeded 10 percent in any sector. The highest rate of default

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND                                  6
was in health care, at 17 percent, followed by consumer discretionary and consumer staples, with
average rates of 11 and 10.3 percent respectively. Default rates in the region were relatively low
(e.g., below 5 percent) for utilities, industries, and financials. (See Table 1.)

Median recovery rates for consumer goods were highest in South Asia (99 percent) followed by
sub-Saharan Africa (97 percent). For financials, the highest median recovery rates were in
sub-Saharan Africa for financials (99.5 percent) and South Asia (98.5 percent). Two regions
registered 100 percent recovery rates for materials: South Asia and LAC.

Data are also provided for communication services, consumer staples, energy, health care,
industrials, IT, real estate, and utilities, but it is more sporadic.

Table 1: How do average private loan default rates vary across regions and industries?
Average annual private loan default rates across World Bank regions and industry sectors, 19942024

Region                      Communicaton
East Asia & Pacific            services (%)
Europe & Central Asia                  Consumer
Latin America & Caribbean                  discretionary (%)
Middle East & North Africa                         Consumer
South Asia                                             staples (%)
Sub-Saharan Africa                                               Energy (%)
                                                                             Financials (%)
                                                                                         Health care (%)
                                                                                                     Industrials (%)
                                                                                                               Information
                                                                                                                  technology (%)
                                                                                                                             Materials (%)
                                                                                                                                         Real estate (%)
                                                                                                                                                     Utilities (%)
                                                                                                                                                                Other (%)

                            3.18  5.62                 4.19  2.56              3   3.23   5.39  2.65  6.63   4.27   1.16  7.69
                            1.76  4.66                 4.41  1.66           1.12   4.51   3.61        3.59   6.10  4.21   2.99
                             3.4                       4.27  5.06          1.97    5.85   2.42        3.57         3.48   3.78
                                    3.3                4.74                3.84      3.6   6.7               6.88
                            3.88  6.64                 3.02  5.24          2.82    5.22   3.19            4           .5  5.67
                            6.42  7.64                10.27                3.96   16.56   4.48        4.52         1.75
                                  11.06                                                               6.84         4.64

Source: Global Emerging Markets Risk Database.
Data not available for Administration sector.

Table 2: How do average private loan recovery rates vary across regions and industries?
Average private loan recovery rates across World Bank regions and industry sectors, 19942024

Region                      Communicaton
                               services (%)
                                         Consumer
                                            discretionary (%)
                                                      Consumer
                                                         staples (%)
                                                                    Energy (%)
                                                                                  Financials (%)
                                                                                               Health care (%)
                                                                                                            Industrials (%)
                                                                                                                         Materials (%)
                                                                                                                                      Real estate (%)
                                                                                                                                                   Utilities (%)
                                                                                                                                                                Other (%)

East Asia & Pacific                             67.1 66.7                  69.1                       68.1                73.4

Europe & Central Asia                           69.2 72.6    53                   77 66.4 66.9        75     71.2  67.5 76.4

Latin America & Caribbean                       63.5 63.7                  55.9 90.3 69.5 85.2                     73.3 69.3

Middle East & North Africa                      66.2                       70.7                 46.7 84.5                 75

South Asia                                      66.2                       83.3                       77.4         68

Sub-Saharan Africa          87.1 72.6 69.2 70.8 90.7                                            70.1 61.2          81.9 78.8

Source: Global Emerging Markets Risk Database.
Data not available for Administration and Information Technology sectors.

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND                                                           7
The maps below show default and recovery rates by country, where available. It correlates largely
with the regional data but there are some interesting outliers, notably Myanmar (15.26 percent) and
Turkmenistan (13.64 percent).

Figure 6: Average default rate for private loans across countries was ~3.5 percent
Average private loan default rates by country, 19942024

Source: Global Emerging Markets Risk Database.

Figure 7: The average private loan recovery rate across countries was 72.9 percent
Average private loan recovery rates by country, 19942024

Source: Global Emerging Markets Risk Database.

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND  8
Default and recovery rates by creditor--a closer look

Average default rates across lending type over three decades show a broad downward trend, though
with spikes during periods of stress (see Figure 8). Private and SOE default rates peaked around the
turn-of-the-century financial crises in Latin America and East Asia, surpassing 8 percent for public
and private borrowers, and subsequently remained at or below 4 percent, except for a jump in 2020
when private defaults reached an average of 5 percent.

Figure 8: How do GEMs default rates compare between different types of
creditors?
Average default rates by creditor type: public, private, and sovereign and
sovereign-guaranteed (1994-2024)

Source: Global Emerging Markets Risk Database.

Recovery rates show a similar pattern, with exceptionally high rates for sovereign lending and lower
rates for SOEs and private lending. Aside from a dip in the mid-1990s for private lending, average
recovery rates for all categories never fell below 60 percent. For sovereign data, rates hovered at or
near 100 percent.

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND  9
Figure 9: How do GEMs recovery rates compare between different types of
creditors?

Recovery rates by creditor type: public, private, and sovereign and sovereign-
guaranteed* (1994-2024)

Source: Global Emerging Markets Risk Database *The sovereign and sovereign-guaranteed line is dotted because there is no
data for some years due to small sample size or lack of defaults.

While the sovereign data results should not come as a surprise, the data for private and SOE lending
may help shift perceptions about the risk of doing business in emerging and developing economies.
To recap, key findings are:

 For state-owned enterprises (i.e., publicly guaranteed debt), default and recovery rates averaged
    2.6 percent and 88 percent respectively between 1994 and 2024.

 For the private sector, default rates averaged 3.5 percent and recovery rates averaged 73 percent,
    although median recovery rates were above 90 percent. The average SSA default rate is
    comparable to that of S&P B to B- rated companies in advanced countries.

 There is some correlation between income levels and default rates, with higher rates prevailing in
    sub-Saharan Africa. But recoveries in sub-Saharan Africa are also higher than averages for other
    regions.

 Gaps in the data on sector-level default rates make it difficult to come to any definitive conclusions
    around risk. There are three sector categories where data are available for all regions: consumer
    goods, financials and materials. The data suggest that risks in financials are especially low, with
    average default rates ranging from 2 to 4 percent, followed by materials (where rates range from
    46.8 percent) and consumer spending (3.3 to 11 percent).

Private investors can benefit from the elements that underpin strong default and recovery rates
(e.g., preferred creditor status and well collateralized deals) by co-investing with MDBs and DFIs.

GEMS AND THE 600800 BILLION DOLL AR DATA DIVIDEND                              10
Moving forward

In addition to shifting private sector risk perceptions, GEMs data are critical for determining how much
capital (equity) DFIs and MDBs need to hold against possible credit losses for all lending categories.
Until recently, CRAs have not had access to the detailed default and recovery data that would allow
them to properly access the risk of MDB loans and therefore accurately calculate MDB capital
requirements. CRAs have been relying on proxy data in many instances, especially for private lending
and recovery rates. Using the GEMs data, S&P's model now suggests that the MDBs can lend over time
up to an additional $800 billion backed by the equity MDBs already have on hand. That is a major
finding in a world where shareholders are increasingly reluctant to fund further MDB capital increases.
Both Moody's and Fitch, with their different methodologies, would do well to re-run their MDB models
using these new data to update and improve the accuracy of their risk weights for MDB portfolios.

As rating agencies produce reports showing large volumes of additional lending headroom, MDB
shareholders and management will have the final say in the matter. Shareholders have a responsibility
to use the capital funded by their taxpayers both prudently and efficiently. The credit rating agencies
have assigned high ratings (often AAA) to these institutions, affirming that they do have strong
prudential controls. But more progress is needed on efficiency, which requires MDBs to put their
additional headroom to use by increasing lending levels. What's also needed now is continued attention
and resolve from the stakeholders who championed the public release of the GEMs data. Specifically,
they should continue to press for a stand-alone, searchable database and elimination or revision of
non-disclosure agreements that preclude more granular data dissemination. Stakeholders can use
G20 and G7 communiques and other joint statements to focus attention and drive more progress.

Using the power of MDBs' own data to unlock lending capacity costs very little while yielding a great
deal, and is in the interest of all shareholders, whether from borrowing countries or creditor countries.
With this latest release, the GEMs consortium has effectively displayed the power of data disclosure,
underscoring why transparency should remain a priority for all stakeholders in the development
finance community.

We would like to thank Nancy Lee for her very helpful suggestions and comments.

KAREN MATHIASEN is a project director with the Center for Global Development.
NICO MARTINEZ is a research assistant at the Center for Global Development.

Suggested citation:
Karen Mathiasen and Nico Martinez. 2025. "GEMs and the 600800 Billion Dollar Data Dividend."
CGD Note 385. Washington, DC: Center for Global Development. https://www.cgdev.org/publication/
gems-and-600-800-billion-dollar-data-dividend

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